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Mohd Yusuf

@mohdyusuf

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I build AI-powered RAG, computer vision, and real-time machine learning applications.

India

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What I'm looking for

I'm looking to build practical AI and machine learning products, especially RAG, computer vision, and real-time applications, while growing as an engineer.

I've built AI-powered products across medical assistance, industrial knowledge intelligence, driver safety, and pronunciation coaching. At Tricon Infotech, I architected a RAG medical assistant and developed FastAPI APIs with token-level streaming that improved response latency by 66.7%.

Through internships at Edunet Foundation and Code Spectra, I trained a 17M-parameter agricultural disease CNN achieving 97% validation accuracy and built computer vision and recommendation systems. I work across Python, FastAPI, React, RAG, TensorFlow, PyTorch, OpenCV, and PostgreSQL to deliver responsive ML applications.

Experience

Work history, roles, and key accomplishments

Software Engineer Intern

Tricon Infotech

Oct 2025 - Mar 2026 (5 months)

Architected an AI-powered medical assistant using Retrieval-Augmented Generation (RAG) to retrieve verified medical knowledge. Developed FastAPI backend APIs with token-level streaming, improving response latency by 66.7%.

RAG fastAPI Python AI Backend Development API Development

Machine Learning Intern

Edunet Foundation

Jan 2025 - Feb 2025 (1 month)

Designed and trained a custom 17M-parameter CNN for agricultural disease detection, achieving 97% validation accuracy. Deployed the model using Streamlit for real-time prediction.

CNN TensorFlow Python Streamlit Machine Learning Deep Learning

Machine Learning Intern

Code Spectra

Jan 2024 - Feb 2024 (1 month)

Engineered a computer vision system for vehicle and pedestrian detection using OpenCV and Haar Cascade Classifiers. Developed a movie recommender system using Cosine Similarity and Scikit-learn.

OpenCV Haar Cascades Computer Vision scikit learn Python Recommendation Systems